Surgical robot positioning methods, positioning devices, robots, and storage media

Abstract

This invention discloses a surgical robot positioning method, positioning device, robot, and storage medium. The surgical robot positioning method includes: acquiring user gesture information; acquiring motion commands and target position information of the surgical robot based on the gesture information; and realizing automatic positioning of the robot based on the motion commands and the target position information. This application uses gesture interaction as the method to specify the desired target position of the robot. It utilizes a mixed reality device to recognize gestures to obtain motion commands and locate the target position in its coordinate space. By combining the coordinate system transformation relationship between the mixed reality device and the robotic arm, the robotic arm can autonomously move to the designated position, realizing convenient positioning of the robotic arm.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, and in particular to a surgical robot positioning method, positioning device, robot, and storage medium. Background Technology

[0002] Currently, surgical robots, especially multi-arm robots, typically require users to drag the robotic arm to the surgical site during preoperative positioning. This manual dragging process is cumbersome, and subsequent surgery can only proceed after the robotic arm is dragged to the surgical site and connected to the cannula. This is not user-friendly or convenient. Existing technologies have also proposed displaying the target position to be positioned in the user's field of vision using augmented reality. The robotic arm is then dragged to the target position based on the displayed target position. However, vision-based fully automatic positioning methods are limited by recognition accuracy and positioning precision, making it difficult to achieve completely autonomous positioning. In addition, additional markers are usually needed to be affixed to the surgical site to assist in the positioning function. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to overcome the cumbersome dragging process of the robot preoperative positioning in the prior art, and to provide a surgical robot positioning method, positioning device, robot and storage medium.

[0004] The present invention solves the above-mentioned technical problems through the following technical solution:

[0005] In a first aspect, a method for positioning a surgical robot is provided, the method comprising:

[0006] Obtain the user's gesture information;

[0007] Based on the gesture information, the movement commands and target position information of the surgical robot are obtained;

[0008] The robot can be automatically positioned based on the motion commands and the target position information.

[0009] Preferably, obtaining the user's gesture information includes:

[0010] Use recognition devices to obtain users' gesture information.

[0011] Preferably, the step of obtaining the movement commands and target position information of the surgical robot based on the gesture information includes:

[0012] A database is pre-built that maps gesture information to movement commands one-to-one;

[0013] The acquired gesture information is matched with gestures in the database to obtain the motion command corresponding to the gesture information.

[0014] Preferably, the step of obtaining the movement commands and target position information of the surgical robot based on the gesture information includes:

[0015] Receive the position information of the gesture in the coordinate system of the recognition device, acquired by the recognition device;

[0016] The position information in the coordinate system of the identification device is converted into the target position information in the coordinate system of the robot.

[0017] Preferably, the step of converting the target position in the recognition device coordinate system into target position information in the robot coordinate system includes:

[0018] Obtain the spatial transfer matrix between the robot coordinate system and the recognition device coordinate system;

[0019] The position information in the coordinate system of the identification device is transformed according to the spatial transfer matrix to obtain the target position information in the robot coordinate system.

[0020] Preferably, obtaining the spatial transition matrix between the robot coordinate system and the recognition device coordinate system specifically includes:

[0021] At least one marker point is set on any movable joint of the surgical robot arm, and the robot arm is controlled to move from a first position state to a second position state.

[0022] Acquire the first end-effector position information in the first position state and the second end-effector position information in the second position state of the robotic arm in the robot coordinate system;

[0023] Receive the first identification position information of the marker point in the first position state and the second identification position information in the second position state in the coordinate system of the identification device;

[0024] The spatial transfer matrix between the robot coordinate system and the recognition device coordinate system is calculated based on the first end position information, the second end position information, the first recognition position information, and the second recognition position information.

[0025] Preferably, the recognition device is a wearable mixed reality device.

[0026] Secondly, a positioning device is provided for implementing the above-described surgical robot positioning method, comprising:

[0027] The gesture information acquisition module is used to acquire the user's gesture information;

[0028] The operation information acquisition module is used to acquire the movement commands and target position information of the surgical robot based on the gesture information;

[0029] The positioning module is used to automatically position the robot based on the motion command and the target position information.

[0030] Thirdly, a robot is provided, including the positioning device described above.

[0031] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the above-described surgical robot positioning method.

[0032] The positive and progressive effects of this invention are as follows:

[0033] This application uses gesture interaction as the way to specify the desired target position for the robot. It uses a mixed reality device to recognize gestures to obtain motion commands and locate the target's position in its coordinate space. Then, by combining the coordinate system transformation relationship between the mixed reality device and the robot, the robot's robotic arm can move autonomously to the specified position, realizing convenient positioning of the robotic arm. Attached Figure Description

[0034] Figure 1 This is a flowchart of the surgical robot positioning method according to Embodiment 1 of the present invention.

[0035] Figure 2 This is a flowchart of motion command acquisition in the surgical robot positioning method of Embodiment 1 of the present invention.

[0036] Figure 3 This is a flowchart of the target position information acquisition process in the surgical robot positioning method of Embodiment 1 of the present invention.

[0037] Figure 4 This is a flowchart of step 122 in the surgical robot positioning method of Embodiment 1 of the present invention.

[0038] Figure 5 This is a flowchart of step 1221 in the surgical robot positioning method of Embodiment 1 of the present invention.

[0039] Figure 6 This is a schematic diagram of the placement device according to Embodiment 2 of the present invention.

[0040] Figure 7 This is a schematic diagram of the operation information acquisition module in the placement device of Embodiment 2 of the present invention. Detailed Implementation

[0041] The present invention will be further illustrated by way of embodiments below, but the present invention is not limited to the scope of the embodiments described herein.

[0042] Example 1

[0043] Surgical robots are increasingly used due to their advantages of less bleeding and faster recovery. A surgical robot includes an operating cart, a vision cart, and a surgeon's console. Before using the surgical robot, the operating cart needs to be moved to the appropriate surgical position. The operating cart can arrive at the operating table automatically or manually. Then, the robotic arm on the operating cart needs to be moved to the patient's lesion area for surgery. In existing technologies, the operator usually manually drags the robotic arm to the surgical position. This method requires manual operation and has poor autonomy and flexibility. Existing technologies also use vision to acquire the patient's lesion area to achieve automatic positioning of the robotic arm, but the accuracy of visual navigation in acquiring spatial position is affected by the accuracy of visual positioning and requires pre-setting corresponding navigation markers. To achieve accurate automatic positioning of the surgical robot, this embodiment proposes a method for more accurately acquiring the surgical position to achieve automatic positioning of the surgical robot.

[0044] A surgical robot positioning method, such as Figure 1 As shown, the method includes:

[0045] Step 10: Obtain the user's gesture information;

[0046] In step 10, the user's gesture information is obtained using a recognition device.

[0047] The recognition device is a wearable mixed reality device, which can be any of the following: a binocular camera, an AR device, a VR device, or a MR device. This embodiment uses a wearable mixed reality device, which facilitates user interaction and has fewer restrictions on the interaction area. However, this embodiment is not limited to wearable devices. The recognition device is mainly used to recognize gestures and locate their positions. Binocular tracking devices and other devices capable of performing these functions can also be applied to this embodiment.

[0048] Step 11: Obtain the movement commands and target position information of the surgical robot based on gesture information;

[0049] Step 12: Automatically position the robot based on motion commands and target position information.

[0050] It should be noted that other methods can also be used to determine the location information of the target. For example, by combining voice control with gestures, the voice commands in the voice information can be directly extracted and used as movement commands. In this way, it is not necessary to recognize specific gestures to obtain the corresponding movement commands, and the spatial target position can be determined by the position of the hand.

[0051] In an alternative implementation, such as Figure 2 As shown, a specific implementation method for obtaining motion commands in step 11 is provided, which specifically includes:

[0052] Step 111: Pre-build a database that maps gesture information to motion commands one-to-one;

[0053] Step 112: Match the acquired gesture information with the gestures in the database to obtain the motion command corresponding to the gesture information.

[0054] One approach is to use a constructed database to match images and find the image with the highest matching degree, thereby determining the motion command corresponding to the gesture. Alternatively, a more intelligent recognition method can be used, such as training based on multiple training images and corresponding motion command labels to obtain a gesture recognition model, and then using the trained model to recognize and output the corresponding motion command in real time.

[0055] In an alternative implementation, such as Figure 3 As shown, the specific implementation method for obtaining target location information in step 11 is provided, which includes:

[0056] Step 121: Receive the position information of the gesture in the coordinate system of the recognition device;

[0057] Step 122: Convert the position information in the recognition device coordinate system into the target position information in the robot coordinate system.

[0058] Among them, such as Figure 4 As shown, step 122 specifically includes:

[0059] Step 1221: Obtain the spatial transfer matrix between the robot coordinate system and the recognition device coordinate system;

[0060] Step 1222: Transform the position information in the recognition device coordinate system according to the spatial transfer matrix to obtain the target position information in the robot coordinate system.

[0061] Among them, such as Figure 5 As shown, step 1221 specifically includes:

[0062] Step 12211: Set at least one marker point on any movable joint of the surgical robot arm, and control the robot arm to move from the first position state to the second position state;

[0063] Step 12212: Obtain the first end-effector position information in the first position state and the second end-effector position information in the second position state of the robot arm in the robot coordinate system;

[0064] Step 12213: Receive the first identification position information of the marker point in the first position state and the second identification position information in the second position state in the coordinate system of the identification device.

[0065] Step 12214: Calculate the spatial transfer matrix between the robot coordinate system and the recognition device coordinate system based on the first end position information, the second end position information, the first recognition position information, and the second recognition position information.

[0066] Specifically, taking a mixed reality device as an example, the mixed reality device is initially placed stationary. A mixed reality marker is fixed on the movable joint of the robotic arm. The robotic arm is then moved arbitrarily twice, from the first position state to the second position state, to obtain the first end-effector position information of the robotic arm in the robot coordinate system in the two position states. Second end position information Then, based on the position information of the two ends, the transformation matrix of the robotic arm end effector in the robot coordinate system is calculated. This matrix can be calculated via the robotic arm console; then, the first recognition position information of the mixed reality marker in two positions in space is acquired by the camera of the mixed reality device. Second identification location information The transformation matrix of the mixed reality marker in the coordinate system of the recognition device is calculated based on the two recognition position information using attitude solving algorithms such as PNP and P3P. Furthermore, considering the principle that the spatial transfer matrix between the robotic arm's end effector and the hybrid marker remains unchanged across different positional states, the spatial transfer matrix X between the hybrid reality marker and the robotic arm's end effector can be calculated. Specifically, X is solved by T_Robot_END*X = X*T_Camera_Marker. After calibration, the spatial position in the recognition device coordinate system can be transformed to the robot coordinate system. To further improve the accuracy of the matrix calculation, the robotic arm can have multiple motion position states, acquiring position information from multiple robotic arm end effectors, and employing redundant calculations to enhance computational accuracy.

[0067] In this example, after obtaining the spatial transition matrix, in the actual application process, the user wears a mixed reality device. The mixed reality device is responsible for recognizing gestures and calculating the coordinate values ​​of the gestures in the mixed reality device space (the fingertips can be selected as the origin of the coordinate system). The mixed reality device extracts the features of the hand and the gesture contour. The corresponding motion instructions in the gesture information are obtained by matching with the database. The gesture coordinate values ​​in the mixed reality device coordinate system are transformed to the robotic arm coordinate system according to the spatial transition matrix. The robotic arm performs inverse kinematics based on the target position and moves autonomously to the target position according to the result.

[0068] It should also be noted that after the robotic arm has moved into position autonomously, if there is a positional deviation between the end of the robotic arm and the target work equipment or device (the user can determine whether the sleeve needle has been reached), the user can manually drag the end of the robotic arm within a small local area to ensure that it is correctly connected to the work equipment or device.

[0069] It should also be noted that this embodiment preferably uses a mixed reality device with self-localization function. When the recognition device moves, the relative movement information of the mixed reality device can be determined through SLAM (Simultaneous Localization and Mapping), and then the new spatial transfer matrix of the mixed reality device and the robot coordinate system after the movement can be obtained. For example, the mixed reality device can be a device with self-localization function such as HoloLens.

[0070] In the above examples, a mixed reality device with self-localization function was mainly used. However, a device without self-localization function, such as a regular monocular camera, can also be used. As long as the user's gesture and the mixed reality marker are both within the imaging range of the device, the position information of the gesture in the robot coordinate system can be calculated.

[0071] In this embodiment, gesture interaction is used to specify the desired target position for the robot. The mixed reality device recognizes the gesture to obtain the motion command and locates the target's position in its coordinate space. Then, combined with the coordinate system transformation relationship between the mixed reality device and the robot, the robot's robotic arm can move autonomously to the specified position, realizing convenient positioning of the robotic arm.

[0072] Example 2

[0073] A positioning device is provided for implementing the surgical robot positioning method described in Embodiment 1, such as... Figure 6 As shown, it includes:

[0074] Gesture information acquisition module 1 is used to acquire the user's gesture information;

[0075] The recognition device is a wearable mixed reality device, which can be any of the following: a binocular camera, an AR device, a VR device, or a MR device.

[0076] The wearable mixed reality device used in this embodiment is convenient for user interaction and has few restrictions on the interaction area. However, this embodiment is not limited to wearable devices. The recognition device is mainly used to recognize gestures and locate the gesture position. Binocular tracking devices that can achieve these functions can also be applied to this embodiment.

[0077] Operation information acquisition module 2 is used to acquire the movement commands and target position information of the surgical robot based on the gesture information;

[0078] Positioning module 3 is used to automatically position the robot based on the motion command and the target position information.

[0079] It should be noted that other methods can also be used to determine the location information of the target. For example, by combining voice control with gestures, the voice commands in the voice information can be directly extracted and used as movement commands. In this way, it is not necessary to recognize specific gestures to obtain the corresponding movement commands, and the spatial target position can be determined by the position of the hand.

[0080] In an alternative implementation, such as Figure 7 As shown, the operation information acquisition module 2 specifically includes:

[0081] Database construction unit 21 is used to pre-build a database that maps gesture information to movement commands one by one;

[0082] The matching unit 22 is used to match the acquired gesture information with the gestures in the database to obtain the motion command corresponding to the gesture information.

[0083] One approach is to use a constructed database to match images and find the image with the highest matching degree, thereby determining the motion command corresponding to the gesture. Alternatively, a more intelligent recognition method can be used, such as training based on multiple training images and corresponding motion command labels to obtain a gesture recognition model, and then using the trained model to recognize and output the corresponding motion command in real time.

[0084] In an alternative implementation, see Figure 7 The operation information acquisition module 2 also includes:

[0085] The recognition location acquisition unit 23 is used to receive the position information of the gesture in the recognition device coordinate system acquired by the recognition device;

[0086] The conversion unit 24 is used to convert the position information in the recognition device coordinate system into the target position information in the robot coordinate system.

[0087] In an alternative implementation, see Figure 7 The operation information acquisition module 2 also includes:

[0088] The spatial transfer matrix acquisition unit 25 is used to acquire the spatial transfer matrix between the robot coordinate system and the recognition device coordinate system;

[0089] The conversion unit 24 is specifically used to convert the position information in the coordinate system of the recognition device according to the spatial transfer matrix to obtain the target position information in the robot coordinate system.

[0090] In an optional implementation, the spatial transition matrix acquisition unit 25 acquires the spatial transition matrix in the following manner:

[0091] At least one marker point is set on any movable joint of the surgical robot arm, and the robot arm is controlled to move from a first position state to a second position state.

[0092] Acquire the first end-effector position information in the first position state and the second end-effector position information in the second position state of the robotic arm in the robot coordinate system;

[0093] The device receives the first identification position information of the marker point in the first position state and the second identification position information in the second position state in the coordinate system of the identification device.

[0094] The spatial transfer matrix between the robot coordinate system and the recognition device coordinate system is calculated based on the first end position information, the second end position information, the first recognition position information, and the second recognition position information.

[0095] Specifically, taking a mixed reality device as an example, the mixed reality device is initially placed stationary. A mixed reality marker is fixed on the movable joint of the robotic arm. The robotic arm is then moved arbitrarily twice, from the first position state to the second position state, to obtain the first end-effector position information of the robotic arm in the robot coordinate system in the two position states. Second end position information Then, based on the position information of the two ends, the transformation matrix of the robotic arm end effector in the robot coordinate system is calculated. This matrix can be calculated via the robotic arm console; then, the first recognition position information of the mixed reality marker in two positions in space is acquired by the camera of the mixed reality device. Second identification location information The transformation matrix of the mixed reality marker in the coordinate system of the recognition device is calculated based on the two recognition position information using attitude solving algorithms such as PNP and P3P. Furthermore, considering the principle that the spatial transfer matrix between the robotic arm's end effector and the hybrid marker remains unchanged across different positional states, the spatial transfer matrix X between the hybrid reality marker and the robotic arm's end effector can be calculated. Specifically, X is solved by T_Robot_END*X = X*T_Camera_Marker. After calibration, the spatial position in the recognition device coordinate system can be transformed to the robot coordinate system. To further improve the accuracy of the matrix calculation, the robotic arm can have multiple motion position states, acquiring position information from multiple robotic arm end effectors, and employing redundant calculations to enhance computational accuracy.

[0096] In this example, after obtaining the spatial transition matrix, in the actual application process, the user wears a mixed reality device. The mixed reality device is responsible for recognizing gestures and calculating the coordinate values ​​of the gestures in the mixed reality device space (the fingertips can be selected as the origin of the coordinate system). The mixed reality device extracts the features of the hand and the gesture contour. The corresponding motion instructions in the gesture information are obtained by matching with the database. The gesture coordinate values ​​in the mixed reality device coordinate system are transformed to the robotic arm coordinate system according to the spatial transition matrix. The robotic arm performs inverse kinematics based on the target position and moves autonomously to the target position according to the result.

[0097] It should also be noted that after the robotic arm has moved into position autonomously, if there is a positional deviation between the end of the robotic arm and the target work equipment or device (the user can determine whether the sleeve needle has been reached), the user can manually drag the end of the robotic arm within a small local area to ensure that it is correctly connected to the work equipment or device.

[0098] It should also be noted that this embodiment preferably uses a mixed reality device with self-localization function. When the recognition device moves, SLAM can also determine the relative movement information of the mixed reality device, and then obtain the new spatial transfer matrix of its coordinate system with the robot after the movement. For example, the mixed reality device can be a device with self-localization function such as HoloLens.

[0099] In the above examples, a mixed reality device with self-localization function was mainly used. However, a device without self-localization function, such as a regular monocular camera, can also be used. As long as the user's gesture and the mixed reality marker are both within the imaging range of the device, the position information of the gesture in the robot coordinate system can be calculated.

[0100] This embodiment also provides a robot, including the positioning device described above.

[0101] In this embodiment, gesture interaction is used to specify the desired target position for the robot. The mixed reality device recognizes the gesture to obtain the motion command and locates the target's position in its coordinate space. Then, combined with the coordinate system transformation relationship between the mixed reality device and the robot, the robot's robotic arm can move autonomously to the specified position, realizing convenient positioning of the robotic arm.

[0102] Example 3

[0103] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the robot positioning guidance method described in Embodiment 1.

[0104] The readable storage medium may be more specifically adopted, including but not limited to: portable disk, hard disk, random access memory, read-only memory, erasable programmable read-only memory, optical storage device, magnetic storage device, or any suitable combination thereof.

[0105] In a possible implementation, the present invention can also be implemented as a program product comprising program code, which, when the program product is run on a terminal device, is used to cause the terminal device to execute the surgical robot positioning method described in Embodiment 1.

[0106] The program code for executing the present invention can be written in any combination of one or more programming languages. The program code can be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on a remote device.

[0107] Example 4

[0108] A recognition device is provided for recognizing a user's gesture information and sending the gesture information to the positioning device and robot as described in Embodiment 2 or the computer-readable storage medium as described in Embodiment 3.

[0109] The recognition device is a wearable mixed reality device, which can be any of the following: binocular camera, AR device, VR device, or MR device.

[0110] While specific embodiments of the present invention have been described above, those skilled in the art should understand that these are merely illustrative examples, and the scope of protection of the present invention is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but all such changes and modifications fall within the scope of protection of the present invention.

Claims

1. A surgical robotic positioning method, characterized by, The method comprises: Obtaining gesture information of a user; Obtaining movement instructions and target position information of a surgical robot based on the gesture information; Implementing automatic positioning of the robot based on the movement instructions and the target position information; The gesture information and the movement instructions are one-to-one mapped. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information.

2. The surgical robotic positioning method of claim 1, wherein, The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information.

3. The surgical robotic positioning method of claim 1, wherein, The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information.

4. The surgical robotic positioning method of any one of claims 2-3, wherein, The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information.

5. A positioning device for implementing the surgical robot positioning method according to any one of claims 1 to 4, characterized in that, The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. The gesture information is matched with gestures in the database to obtain movement instructions corresponding to the gesture information. 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The gesture information is matched The spatial transfer matrix acquisition unit is configured to acquire a spatial transfer matrix between the robot coordinate system and the recognition device coordinate system. The conversion unit is specifically configured to convert the position information in the recognition device coordinate system according to the spatial transfer matrix to obtain the target position information in the robot coordinate system.

6. A robot, characterized in that The positioning device as claimed in claim 5.

7. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by a processor to implement the surgical robot positioning method of any one of claims 1 to 4. The computer program is executed by a processor to implement the surgical robot positioning method of any one of claims 1 to 4.

Images